The sheer number and complexity of contracts that a company may enter into results in difficulties in contract management. Large companies may have between 10,000 and 40,000 active contracts. Because these contracts are typically scattered throughout an organization within filing cabinets and individual computers, the business-critical information contained in the contracts, such as payment terms, renewal clauses, liabilities, etc., are hidden from view.
Some of the biggest barriers to successful implementations of contract management solutions are data availability and data quality. For a contract management solution to be effective, the content of paper and computer-based documents must be converted into useable, consistent digitized data. Contract managers typically gather this critical contract data through the difficult and time-consuming process of data conversion and extraction.
Data conversion, or the process of extracting existing data from other applications and converting it into a useable format, is important because certain types of data are more accurate when pulled from applications. However, data conversion alone falls short of the rich data fields that are created during the data extraction process.
Data abstraction is the process of extracting or summarizing key data from contracts and converting the data into consistent electronic formats. This data can be stored in a centralized data repository (application database) where it can be accessed by a contract management solution. Data abstraction focuses on both the quantitative and qualitative information contained in contracts. Quantitative information, data with measurable terms, is essential to the execution and management of contracts. This information can include items such as payment terms, renewal clauses, liabilities, discounts and other incentives, chargeback terms and revenue recognition. Qualitative information, or data about the specific elements of a contract, can be essential to understanding the contract as a whole and can include items such as critical issues, key clauses, responsibilities, and descriptive information about quantitative fields.
By extracting and consolidating key information from contracts, companies are able to build a comprehensive view of all the contractual obligations that drive their operations and spending. Because data abstraction is a difficult process involving high degrees of complexity, and because a company may have large numbers of contracts, few companies or system implementers are equipped to handle the job.